Skip to main content
Glama
Sign In
WTFM

WTFM

Official
by SupportPages-io
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Local

supportpages_review_recommendations

Destructive

Accept or reject a suggested article recommendation; use create_article with the recommendation_id to generate an accepted article.

Instructions

Accept or reject one selected suggestion. Acceptance never advances onboarding or starts generation. Generate an accepted article recommendation explicitly with create_article and recommendation_id.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "id": "<id>",
      "decision": "<decision>"
    },
    "name": "supportpages_review_recommendations"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYes
decisionYes
workspaceNo

Output Schema

NameRequiredDescriptionDefault
errorNo
resultNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.7

TDQS

B3.4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=false, destructiveHint=true, and openWorldHint=true, so the mutation/irreversibility profile is partly covered. The description usefully adds that acceptance has no side effect on onboarding or generation. However, it does not explain the reversibility of a reject decision, permission requirements, or that this is a state-changing call, leaving meaningful behavior gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences, front-loaded with the core action and following with the key constraint and the follow-up tool. No filler; each sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need not be described. The description covers purpose and the important no-side-effect caveat, but leaves the three parameters unexplained, which is a notable gap for a state-changing tool with 0% schema coverage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description carries the burden of explaining id, decision, and workspace. It does not clarify what id refers to (the recommendation id?), that decision must be accept/reject, or what workspace does. The mention of recommendation_id pertains to a different tool (create_article), not this tool's parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action pair (accept or reject) applied to a single selected suggestion/recommendation. It is clear this is a decision tool rather than a listing tool. It does not explicitly name sibling tools like list_recommendations or recommend_articles to sharpen the boundary, so it stops short of 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives useful context: acceptance does not advance onboarding or start generation, and to actually generate an accepted recommendation you use create_article with recommendation_id. That is clear when-to-use routing, though it lacks explicit when-not conditions for reject or workspace scoping.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

Other Tools